Electrovaya Inc (ELVA) Fair Value & Analysis
Industrials · US · Market cap $516M
Analysis
Electrovaya Inc (ELVA) currently trades at $9.96, while our model-based Fair Value estimate is $1.43 — implying the stock looks roughly 85.6% overvalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: medium).
About the company
Electrovaya Inc. engages in the design, development, manufacture, and sale of lithium-ion batteries, battery management systems, and battery-related products for energy storage, clean electric transportation, and other specialized applications in North America. It operates infinity battery systems comprising of low and high voltage systems. The company also operates solid state battery technology. In addition, it offers lithium-ion battery systems to power MHEV, including fork-lifts, as well as accessories, such as battery chargers to charge the batteries; lithium-ion batteries for robotic applications; lithium ion battery cell and modules for sales to OEM customers in the defense, construction, and other applications; high voltage battery systems for electric bus, truck, and defense applications; and industrial products for energy storage. The company was formerly known as Electrofuel Inc. and changed its name to Electrovaya Inc. in March 2002. Electrovaya Inc. was incorporated in …
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.